Updated Models of Passenger Transport Related Energy Consumption of Urban Areas

Ali Enes Dingil, Joerg Schweizer, Federico Rupi and Zaneta Stasiskiene
Additional contact information
Ali Enes Dingil: Institute of Environmental Engineering, Kaunas University of Technology, Gedimino St. 50, LT-44239 Kaunas, Lithuania
Joerg Schweizer: Transport Engineering Group, Department of Civil, Chemical, Environmental Engineering, University of Bologna, Viale Risorgimento, 2, I-40136 Bologna, Italy
Federico Rupi: Transport Engineering Group, Department of Civil, Chemical, Environmental Engineering, University of Bologna, Viale Risorgimento, 2, I-40136 Bologna, Italy
Zaneta Stasiskiene: Institute of Environmental Engineering, Kaunas University of Technology, Gedimino St. 50, LT-44239 Kaunas, Lithuania

Sustainability, 2019, vol. 11, issue 15, 1-16

Abstract: Introduction: As the global warming threat has become more concrete in recent years, there is a need to update transport energy consumptions of cities and to understand how they relate to population density and transport infrastructure. Transportation is one of the major sources of global warming and this update is an important warning for urban planners and policy makers to take action in a more consistent way. Analysis: This paper estimates and analyzes the passenger transport energy per person per year with a large and diverse sample set based on comparable, directly observable open-source data of 57 cities, distributed over 33 countries. The freight transport energy consumption, which accounts for a large portion of urban transport energy, is not considered. The main focus of the analysis is to establish a quantitative relation between population density, transport infrastructure and transport energy consumption. Results: In a first step, significant linear relations have been found between road length per inhabitant, the road infrastructure accessibility (RIA) and private car mode share as well as between RIA and public transport mode share. Results show further relation between travel distance, population density and RIA. In a second step, a simplified model has been developed that explains the non-linear relation between the population density and RIA. Finally, based on this relation and the above findings, a hyperbolic function between population density and transport energy has been calibrated, which explains the rapid increase of transport energy consumption of cities with low population density. Conclusions: The result of the this study has clearly identified the high private car mode share as main cause for the high transport energy usage of such cities, while the longer average commute distance in low-population density cities has a more modest influence on their transport energy consumption.

Keywords: transport energy; population density; infrastructure accessibility; open source data; OSM; transport policy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/15/4060/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/15/4060/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:15:p:4060-:d:252282

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().